Multivariate approach to classify research institutes according to their outputs: The case of the CSIC's institutes

José Luis Ortega, Elena López-Romero and Inés Fernández

Journal of Informetrics, 2011, vol. 5, issue 3, 323-332

Abstract: This paper attempts to build a classification model according to the research products created by those institutes and hence to design specific evaluation processes. Several scientific input/output indicators belonging to 109 research institutes from the Spanish National Research Council (CSIC) were selected. A multidimensional approach was proposed to resume these indicators in various components. A clustering analysis was used to classify the institutes according to their scores with those components (principal component analysis). Moreover, the validity of the a priori classification was tested and the most discriminant variables were detected (linear discriminant analysis). Results show that there are three types of institutes according to their research outputs: Humanistic, Scientific and Technological. It is argue that these differences oblige to design more precise assessment exercises which focus on the particular results of each type of institute. We conclude that this method permits to build more precise research assessment exercises which consider the varied nature of the scientific activity.

Keywords: Scientometrics; Principal component analysis; Linear discriminant analysis; Research centres classification (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:5:y:2011:i:3:p:323-332

DOI: 10.1016/j.joi.2011.01.004

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